Essential Tremor accentuates the pattern of tremor-band coherence between upper-limb muscles.

Although Essential Tremor is one of the most common movement disorders, current treatment options are relatively limited. Peripheral tremor suppression methods have shown potential, but we do not currently know which muscles are most responsible for patients' tremor, making it difficult to optimize suppression methods. The purpose of this study was to quantify the relationships between the tremorogenic activity in muscles throughout the upper limb. Muscle activity was recorded from the 15 major superficial upper-limb muscles in 24 subjects with Essential Tremor while they held various postures or made upper-limb movements. We calculated the coherence in the tremor band (4-12 Hz) between the activity of all muscle pairs and the time-varying phase difference between sufficiently coherent muscle pairs. Overall, the observed pattern somewhat mirrored functional relationships: agonistic muscle pairs were most coherent and in phase, whereas antagonist and unrelated muscle pairs exhibited less coherence and were either consistently in phase, consistently antiphase, consistently out of phase (unrelated pairs only), or else inconsistent. Patients exhibited significantly more coherence than control subjects (p<0.001) in the vast majority of muscle pairs (95 out of 105). Furthermore, differences between patients and controls were most pronounced among agonists; thus, the coherence pattern existing in control subjects was accentuated in patients with ET. We conclude that tremor-band activity is broadly distributed among the muscles of the upper limb, challenging efforts to determine which muscles are most responsible for a patient's tremor.

Movement preferences of the wrist and forearm during activities of daily living.

BACKGROUND: During activities of daily living, the main degrees of freedom of the forearm and wrist-forearm pronation-supination (PS), wrist flexion-extension (FE), and wrist radial-ulnar deviation (RUD)-combine seamlessly to allow the hand to engage with and manipulate objects in our environment. Yet the combined behavior of these three degrees of freedom is relatively unknown. PURPOSE: To provide a characterization of natural forearm and wrist kinematics (joint configuration, movement direction, and speed) during activities of daily living. STUDY DESIGN: This is a descriptive cross-sectional study. METHODS: Ten healthy subjects performed 24 activities of daily living chosen to represent a wide variety of activities, while we measured their PS, FE, and RUD angles using electromagnetic motion capture. The orientation of the forearm and wrist was represented in the three-dimensional "configuration space" spanned by PS, FE, and RUD. From the time course of forearm and wrist orientation in configuration space, we extracted three-dimensional distributions of joint configuration, movement direction, and speed. RESULTS: Most joint configurations were focused in a relatively small area: subjects spent roughly 50% of the time in the central 20% of their functional range of motion. Some movement directions were significantly more common than others (p < 0.001); in particular, the direction of the dart-thrower's motion (DTM) was about three times more common than motion perpendicular to it. Most movements were slow: the likelihood of moving at increasing speeds dropped off exponentially. Interestingly, the most common high-speed motion combined the DTM with a twist from pronation to supination. As this motion allows one to pick up an object in front of one's body and bring it to the head, it is essential for self-care. Thus, although many activities of daily living follow the DTM without significant forearm rotation, the greatest importance of the DTM may lie in its combination with forearm rotation. CONCLUSIONS: Despite the wide variety of activities, we found evidence of preferred movement behavior, and this behavior showed significant coupling between the wrist and forearm.

Compensating for Soft-Tissue Artifact Using the Orientation of Distal Limb Segments During Electromagnetic Motion Capture of the Upper Limb.

Most motion capture measurements suffer from soft-tissue artifacts (STA). Especially affected are rotations about the long axis of a limb segment, such as humeral internal-external rotation (HIER) and forearm pronation-supination (FPS). Unfortunately, most existing methods to compensate for STA were designed for optoelectronic motion capture systems. We present and evaluate an STA compensation method that (1) compensates for STA in HIER and/or FPS, (2) is developed specifically for electromagnetic motion capture systems, and (3) does not require additional calibration or data. To compensate for STA, calculation of HIER angles relies on forearm orientation, and calculation of FPS angles rely on hand orientation. To test this approach, we recorded whole-arm movement data from eight subjects and compared their joint angle trajectories calculated according to progressive levels of STA compensation. Compensated HIER and FPS angles were significantly larger than uncompensated angles. Although the effect of STA compensation on other joint angles (besides HIER and FPS) was usually modest, significant effects were seen in certain degrees-of-freedom under some conditions. Overall, the method functioned as intended during most of the range of motion of the upper limb, but it becomes unstable in extreme elbow extension and extreme wrist flexion-extension. Specifically, this method is not recommended for movements within 20 deg of full elbow extension, full wrist flexion, or full wrist extension. Since this method does not require additional calibration of data, it can be applied retroactively to data collected without the intent to compensate for STA.

Tracking Joint Angles During Whole-Arm Movements Using Electromagnetic Sensors.

Electromagnetic (EM) motion tracking systems are suitable for many research and clinical applications, including in vivo measurements of whole-arm movements. Unfortunately, the methodology for in vivo measurements of whole-arm movements using EM sensors is not well described in the literature, making it difficult to perform new measurements and all but impossible to make meaningful comparisons between studies. The recommendations of the International Society of Biomechanics (ISB) have provided a great service, but by necessity they do not provide clear guidance or standardization on all required steps. The goal of this paper was to provide a comprehensive methodology for using EM sensors to measure whole-arm movements in vivo. We selected methodological details from past studies that were compatible with the ISB recommendations and suitable for measuring whole-arm movements using EM sensors, filling in gaps with recommendations from our own past experiments. The presented methodology includes recommendations for defining coordinate systems (CSs) and joint angles, placing sensors, performing sensor-to-body calibration, calculating rotation matrices from sensor data, and extracting unique joint angles from rotation matrices. We present this process, including all equations, for both the right and left upper limbs, models with nine or seven degrees-of-freedom (DOF), and two different calibration methods. Providing a detailed methodology for the entire process in one location promotes replicability of studies by allowing researchers to clearly define their experimental methods. It is hoped that this paper will simplify new investigations of whole-arm movement using EM sensors and facilitate comparison between studies.

Voluntary and tremorogenic inputs to motor neuron pools of agonist/antagonist muscles in essential tremor patients.

Pathological tremor is an oscillation of body parts at 3-10 Hz, determined by the output of spinal motor neurons (MNs), which receive synaptic inputs from supraspinal centers and muscle afferents. The behavior of spinal MNs during tremor is not well understood, especially in relation to the activation of the multiple muscles involved. Recent studies on patients with essential tremor have shown that antagonist MN pools receive shared input at the tremor frequency. In this study, we investigated the synaptic inputs related to tremor and voluntary movement, and their coordination across antagonist muscles. We analyzed the spike trains of motor units (MUs) identified from high-density surface electromyography from the forearm extensor and flexor muscles in 15 patients with essential tremor during postural tremor. The shared synaptic input was quantified by coherence and phase difference analysis of the spike trains. All pairs of spike trains in each muscle showed coherence peaks at the voluntary drive frequency (1-3 Hz, 0.2 ± 0.2, mean ± SD) and tremor frequency (3-10 Hz, 0.6 ± 0.3) and were synchronized with small phase differences (3.3 ± 25.2° and 3.9 ± 22.0° for the voluntary drive and tremor frequencies, respectively). The coherence between MN spike trains of antagonist muscle groups at the tremor frequency was significantly smaller than intramuscular coherence. We predominantly observed in-phase activation of MUs between agonist/antagonist muscles at the voluntary frequency band (0.6 ± 48.8°) and out-of-phase activation at the tremor frequency band (126.9 ± 75.6°). Thus MNs innervating agonist/antagonist muscles concurrently receive synaptic inputs with different phase shifts in the voluntary and tremor frequency bands.NEW & NOTEWORTHY Although the mechanical characteristics of tremor have been widely studied, the activation of the affected muscles is still poorly understood. We analyzed the behavior of motor units of pairs of antagonistic wrist muscle groups in patients with essential tremor and studied their activity at voluntary movement- and tremor-related frequencies. We found that the phase relation between inputs to antagonistic muscles is different at the voluntary and tremor frequency bands.

Simulated Tremor Propagation in the Upper Limb: From Muscle Activity to Joint Displacement.

Although tremor is the most common movement disorder, there are few noninvasive treatment options. Creating effective tremor suppression devices requires a knowledge of where tremor originates mechanically (which muscles) and how it propagates through the limb (to which degrees-of-freedom (DOF)). To simulate tremor propagation, we created a simple model of the upper limb, with tremorogenic activity in the 15 major superficial muscles as inputs and tremulous joint displacement in the seven major DOF as outputs. The model approximated the muscle excitation-contraction dynamics, musculoskeletal geometry, and mechanical impedance of the limb. From our simulations, we determined fundamental principles for tremor propagation: (1) The distribution of tremor depends strongly on musculoskeletal dynamics. (2) The spreading of tremor is due to inertial coupling (primarily) and musculoskeletal geometry (secondarily). (3) Tremorogenic activity in a given muscle causes significant tremor in only a small subset of DOF, though these affected DOF may be distant from the muscle. (4) Assuming uniform distribution of tremorogenic activity among muscles, tremor increases proximal-distally, and the contribution from muscles increases proximal-distally. (5) Although adding inertia (e.g., with weighted utensils) is often used to suppress tremor, it is possible to increase tremor by adding inertia to the wrong DOF. (6) Similarly, adding viscoelasticity to the wrong DOF can increase tremor. Based solely on the musculoskeletal system, these principles indicate that tremor treatments targeting muscles should focus first on the distal muscles, and devices targeting DOF should focus first on the distal DOF.

Control of redundant pointing movements involving the wrist and forearm.

The musculoskeletal system can move in more ways than are strictly necessary, allowing many tasks to be accomplished with a variety of limb configurations. Why some configurations are preferred has been a focus of motor control research, but most studies have focused on shoulder-elbow or whole arm movements. This study focuses on movements involving forearm pronation-supination (PS), wrist flexion-extension (FE), and wrist radial-ulnar deviation (RUD) and elucidates how these three degrees of freedom (DOF) combine to perform the common task of pointing, which only requires two DOF. Although pointing is more sensitive to FE and RUD than to PS and could be easily accomplished with FE and RUD alone, subjects tend to involve a small amount of PS. However, why we choose this behavior has been unknown and is the focus of this paper. With the use of a second-order model with lumped parameters, we tested a number of plausible control strategies involving minimization of work, potential energy, torque, and path length. None of these control schemes robustly predicted the observed behavior. However, an alternative control scheme, hypothesized to control the DOF that were most important to the task (FE and RUD) and ignore the less important DOF (PS), matched the observed behavior well. In particular, the behavior observed in PS appears to be a mechanical side effect caused by unopposed interaction torques. We conclude that moderately sized pointing movements involving the wrist and forearm are controlled by ignoring forearm rotation even though this strategy does not robustly minimize work, potential energy, torque, or path length. NEW & NOTEWORTHY Many activities require us to point our hands in a given direction using wrist and forearm rotations. Although there are infinitely many ways to do this, we tend to follow a stereotyped pattern. Why we choose this pattern has been unknown and is the focus of this paper. After testing a variety of hypotheses, we conclude that the pattern results from a simplifying strategy in which we focus on wrist rotations and ignore forearm rotation.

Proximal-distal differences in movement smoothness reflect differences in biomechanics.

Smoothness is a hallmark of healthy movement. Past research indicates that smoothness may be a side product of a control strategy that minimizes error. However, this is not the only reason for smooth movements. Our musculoskeletal system itself contributes to movement smoothness: the mechanical impedance (inertia, damping, and stiffness) of our limbs and joints resists sudden change, resulting in a natural smoothing effect. How the biomechanics and neural control interact to result in an observed level of smoothness is not clear. The purpose of this study is to 1) characterize the smoothness of wrist rotations, 2) compare it with the smoothness of planar shoulder-elbow (reaching) movements, and 3) determine the cause of observed differences in smoothness. Ten healthy subjects performed wrist and reaching movements involving different targets, directions, and speeds. We found wrist movements to be significantly less smooth than reaching movements and to vary in smoothness with movement direction. To identify the causes underlying these observations, we tested a number of hypotheses involving differences in bandwidth, signal-dependent noise, speed, impedance anisotropy, and movement duration. Our simulations revealed that proximal-distal differences in smoothness reflect proximal-distal differences in biomechanics: the greater impedance of the shoulder-elbow filters neural noise more than the wrist. In contrast, differences in signal-dependent noise and speed were not sufficiently large to recreate the observed differences in smoothness. We also found that the variation in wrist movement smoothness with direction appear to be caused by, or at least correlated with, differences in movement duration, not impedance anisotropy.NEW & NOTEWORTHY This article presents the first thorough characterization of the smoothness of wrist rotations (flexion-extension and radial-ulnar deviation) and comparison with the smoothness of reaching (shoulder-elbow) movements. We found wrist rotations to be significantly less smooth than reaching movements and determined that this difference reflects proximal-distal differences in biomechanics: the greater impedance (inertia, damping, stiffness) of the shoulder-elbow filters noise in the command signal more than the impedance of the wrist.

Moving slowly is hard for humans: limitations of dynamic primitives.

Mounting evidence suggests that human motor control uses dynamic primitives, attractors of dynamic neuromechanical systems that require minimal central supervision. However, advantages for control may be offset by compromised versatility. Extending recent results showing that humans could not sustain discrete movements as duration decreased, this study tested whether smoothly rhythmic movements could be maintained as duration increased. Participants performed horizontal movements between two targets, paced by sounds with intervals that increased from 1 to 6 s by 200 ms per cycle and then decreased again. The instruction emphasized smooth rhythmic movements without interspersed dwell times. We hypothesized that 1) when oscillatory motions slow down, smoothness decreases; 2) slower oscillatory motions are executed as submovements or even discrete movements; and 3) the transition between smooth oscillations and submovements shows hysteresis. An alternative hypothesis was that 4) removing visual feedback restores smoothness, indicative of visually evoked corrections causing the irregularity. Results showed that humans could not perform slow and smooth oscillatory movements. Harmonicity decreased with longer intervals, and dwell times between cycles appeared and became prominent at slower speeds. Velocity profiles showed an increase with cycle duration of the number of overlapping submovements. There was weak evidence of hysteresis in the transition between these two types of movement. Eliminating vision had no effect, suggesting that intermittent visually evoked corrections did not underlie this phenomenon. These results show that it is hard for humans to execute smooth rhythmic motions very slowly. Instead, they "default" to another dynamic primitive and compose motion as a sequence of overlapping submovements.NEW & NOTEWORTHY Complementing a large body of prior work showing advantages of composing primitives to manage the complexity of motor control, this paper uncovers a limitation due to composition of behavior from dynamic primitives: while slower execution frequently makes a task easier, there is a limit and it is hard for humans to move very slowly. We suggest that this remarkable limitation is not due to inadequacies of muscle, nor to slow neural communication, but is a consequence of how the control of movement is organized.

Hand and distal joint tremor are most coherent with the activity of elbow flexors and wrist extensors in persons with essential tremor.

Essential tremor (ET) affects millions of people. Although frontline treatment options (medication, deep brain stimulation, and focused ultrasound ablation) have provided significant relief, many patients are unsatisfied with the outcomes. Peripheral suppression techniques, such as injections of botulinum toxin or sensory electrical stimulation of muscles, are gaining popularity, but could be optimized if the muscles most responsible for a patient's tremor were identified. The purpose of this study was to quantify the relationship between the activity in various upper limb muscles and the resulting tremor in patients with ET. Surface electromyogram (sEMG) from the 15 major superficial muscles of the upper limb and displacement of the hand and upper limb joints were recorded from 22 persons with ET while they performed kinetic and postural tasks representative of activities of daily living. We calculated the peak coherence (frequency-dependent correlation) in the tremor band (4-8 Hz) between the sEMG of each muscle and the displacement in each major degree of freedom (DOF). Averaged across subjects with ET, the highest coherence was found between elbow flexors (particularly biceps brachii and brachioradialis) and the distal DOF (forearm, wrist, and hand motion), and between wrist extensors (extensor carpi radialis and ulnaris) and the same distal DOF. These coherence values represent the upper bound on the proportion of the tremor caused by each muscle. We conclude that, without further information, elbow flexors and wrist extensors should be among the first muscles considered for peripheral suppression techniques in persons with ET.NEW & NOTEWORTHY We characterized the relationships between activity in upper limb muscles and tremor in persons with essential tremor using coherence, which provides an upper bound on the proportion of the tremor due to each muscle. Averaged across subjects and various tasks, tremor in the hand and distal joints was most coherent with elbow flexors and wrist extensors. We conclude that, without further information, these muscle groups should be among the first considered for peripheral suppression techniques.

Does a basic deficit in force control underlie cerebellar ataxia?

Because damage to the cerebellum results in characteristic movement incoordination known as "ataxia," it has been hypothesized that it is involved in estimation of limb dynamics that occur during movement. However, cerebellar function may extend beyond movement to force control in general, with or without movement. Here we tested whether the cerebellum is involved in controlling force separate from estimating limb dynamics and whether ataxia could result from a deficit in force control. We studied patients with cerebellar ataxia controlling their arm force isometrically; in this condition arm dynamics are absent and there is no need for (or effect from an impairment in) estimations of limb dynamics. Subjects were required to control their force magnitude, direction, or both. Cerebellar patients were able to match force magnitude or direction similarly to control subjects. Furthermore, when controlling force magnitude, they intuitively chose directions (not specified) that required minimal effort at the joint level--this ability was also similar to control subjects. In contrast, cerebellar patients performed significantly worse than control subjects when asked to match both force magnitude and direction. This was surprising, since they did not exhibit significant impairment in doing either in isolation. These results show that cerebellum-dependent computations are not limited to estimations of body dynamics needed for active movement. Deficits occur even in isometric conditions, but apparently only when multiple degrees of freedom must be controlled simultaneously. Thus a fundamental cerebellar operation may be combining/coordinating degrees of freedom across many kinds of movements and behaviors.

Feasibility of using the Leap Motion Controller to administer conventional motor tests: a proof-of-concept study.

Although upper-limb movement impairments are common, the primary tools for assessing and tracking impairments in clinical settings are limited. Markerless motion capture (MMC) technology has the potential to provide a large amount of quantitative, objective movement data in routine clinical use. Many past studies have focused on whether MMC are sufficiently accurate. However, another necessary step is to create meaningful clinical tests that can be administered via MMC in a robust manner. Four conventional upper-limb motor tests common in clinical assessments (visually guided movement, finger tapping, postural tremor, and reaction time) were modified so they can be administered via a particular MMC sensor, the Leap Motion Controller (LMC). In this proof-of-concept study, we administered these modified tests to 100 healthy subjects and present here the successes and challenges we encountered. Subjects generally found the LMC and the graphical user interfaces of the tests easy to use. The LMC recorded movement with sufficiently high sampling rate (>106 samples/s), and the rate of LMC malfunctions (mainly jumps in time or space) was low, so only 1.9% of data was discarded. However, administration of the tests also revealed some significant weaknesses. The visually guided movement test was easily implemented with the LMC; the modified reaction time test worked reasonably well with the LMC but is likely more easily implemented with other existing technologies; and the modified tremor and finger tapping tests did not work well because of the limited bandwidth of the LMC. Our findings highlight the need to develop and evaluate motor tests specifically suited for MMC. The real strength of MMC may not be in replicating conventional tests but rather in administering new tests or testing conditions not possible with conventional clinical tests or other technologies.

The signed helical angle: A technique for characterizing midfoot motion during gait.

Quantifying motion in the midfoot during gait and other movements is important for a variety of applications, but challenging due to the complexity of the multiple small articulations involved. The most common motion capture based techniques are limited in their ability to characterize the non-planar nature of the midfoot joint axes. In this study we developed a novel Signed Helical Angle (SHA) to quantify midfoot angular displacement. Motion capture data from 40 healthy subjects walking at a controlled speed were used to calculate finite helical axes and angles from a two-segment foot model. Axes were classified as either pronation or supination based on their orientation, and given a sign, thus either adding to or subtracting from the angular displacement. Analysis focused on insights from axis orientation and comparisons to other techniques. Results showed that when transitions were excluded, pronation and supination axes were fairly well clustered in the transverse plane. The resulting SHA midfoot angle waveform was comparable to sagittal plane Euler and helical component waveforms, but with 39% (approximately 3°) greater range of motion in pronation and 25% (approximately 4°) greater in supination, due to the direct measurement of the motion path and the influence of the other planes. The proposed SHA method may provide an intuitive and useful method to analyze midfoot motion for a variety of applications, particularly when interventions cause subtle changes that may be diluted in planar analyses.

Brief Submotor-Threshold Electrical Stimulation Applied Synchronously Over Wrist Flexor and Extensor Muscles does Not Suppress Essential Tremor, Independent of Stimulation Frequency.

Background: Electrical stimulation of muscles below motoneuron threshold has shown potential as a low-cost and minimally invasive treatment for Essential Tremor (ET). Prior studies have stimulated wrist flexor and extensor muscles synchronously with diverging results, calling for further investigation. Also, prior studies have only used a narrow range of stimulation parameters, so stimulation parameters have not been optimized. Our purpose was to further investigate synchronous submotor stimulation and identify the effect of stimulation frequency on tremor suppression. Methods: We quantified the effect of brief, synchronous stimulation at 15 different frequencies from 10-150 Hz applied over wrist flexors and extensors on both tremor power and frequency in 20 ET patients. We compared tremor power and frequency from hand acceleration and sEMG between pre-, per-, and post-stimulation phases. Results: Our stimulation paradigm did not result in significant tremor suppression or tremor frequency changes at any tested stimulation frequency, showing no significant interaction between phase and stimulation frequency for tremor power measured by either hand acceleration (p = 0.69) or sEMG (p = 0.07). Additionally, the effect of phase interacting with stimulation frequency on tremor frequency was statistically insignificant for acceleration (p = 0.64) and sEMG (p = 0.37). Discussion: We conclude that brief synchronous submotor-threshold stimulation does not reduce tremor in ET patients, independent of stimulation frequency (from 10 to 150 Hz). Our results are consistent with the hypothesis that brief submotor-threshold stimulation suppresses tremor via reciprocal inhibition, which requires asynchronous stimulation. In contrast, it is hypothesized that synchronous stimulation might require longer stimulation durations to affect supraspinal tremor networks. Highlights: We studied the effects of synchronous submotor electrical stimulation over wrist flexor and extensor muscles on Essential Tremor. Our results indicate that suppressing tremor with brief synchronous stimulation is ineffective. Based on recently hypothesized mechanisms of peripheral tremor suppression, we hypothesize that asynchronous stimulation or long-duration synchronous stimulation are more effective approaches to peripheral tremor suppression.

Stiffness, not inertial coupling, determines path curvature of wrist motions.

When humans rotate their wrist in flexion-extension, radial-ulnar deviation, and combinations, the resulting paths (like the path of a laser pointer on a screen) exhibit a distinctive pattern of curvature. In this report we show that the passive stiffness of the wrist is sufficient to account for this pattern. Simulating the dynamics of wrist rotations using a demonstrably realistic model under a variety of conditions, we show that wrist stiffness can explain all characteristics of the observed pattern of curvature. We also provide evidence against other possible causes. We further demonstrate that the phenomenon is robust against variations in human wrist parameters (inertia, damping, and stiffness) and choice of model inputs. Our findings explain two previously observed phenomena: why faster wrist rotations exhibit more curvature and why path curvature rotates with pronation-supination of the forearm. Our results imply that, as in reaching, path straightness is a goal in the planning and control of wrist rotations. This requires humans to predict and compensate for wrist dynamics, but, unlike reaching, nonlinear inertial coupling (e.g., Coriolis acceleration) is insignificant. The dominant term to be compensated is wrist stiffness.

The passive stiffness of the wrist and forearm.

Because wrist rotation dynamics are dominated by stiffness (Charles SK, Hogan N. J Biomech 44: 614-621, 2011), understanding how humans plan and execute coordinated wrist rotations requires knowledge of the stiffness characteristics of the wrist joint. In the past, the passive stiffness of the wrist joint has been measured in 1 degree of freedom (DOF). Although these 1-DOF measurements inform us of the dynamics the neuromuscular system must overcome to rotate the wrist in pure flexion-extension (FE) or pure radial-ulnar deviation (RUD), the wrist rarely rotates in pure FE or RUD. Instead, understanding natural wrist rotations requires knowledge of wrist stiffness in combinations of FE and RUD. The purpose of this report is to present measurements of passive wrist stiffness throughout the space spanned by FE and RUD. Using a rehabilitation robot designed for the wrist and forearm, we measured the passive stiffness of the wrist joint in 10 subjects in FE, RUD, and combinations. For comparison, we measured the passive stiffness of the forearm (in pronation-supination), as well. Our measurements in pure FE and RUD agreed well with previous 1-DOF measurements. We have linearized the 2-DOF stiffness measurements and present them in the form of stiffness ellipses and as stiffness matrices useful for modeling wrist rotation dynamics. We found that passive wrist stiffness was anisotropic, with greater stiffness in RUD than in FE. We also found that passive wrist stiffness did not align with the anatomical axes of the wrist; the major and minor axes of the stiffness ellipse were rotated with respect to the FE and RUD axes by ∼20°. The direction of least stiffness was between ulnar flexion and radial extension, a direction used in many natural movements (known as the "dart-thrower's motion"), suggesting that the nervous system may take advantage of the direction of least stiffness for common wrist rotations.

Online Tracking of the Phase Difference Between Neural Drives to Antagonist Muscle Pairs in Essential Tremor Patients.

Transcutaneous electrical stimulation has been applied in tremor suppression applications. Out-of-phase stimulation strategies applied above or below motor threshold result in a significant attenuation of pathological tremor. For stimulation to be properly timed, the varying phase relationship between agonist-antagonist muscle activity during tremor needs to be accurately estimated in real-time. Here we propose an online tremor phase and frequency tracking technique for the customized control of electrical stimulation, based on a phase-locked loop (PLL) system applied to the estimated neural drive to muscles. Surface electromyography signals were recorded from the wrist extensor and flexor muscle groups of 13 essential tremor patients during postural tremor. The EMG signals were pre-processed and decomposed online and offline via the convolution kernel compensation algorithm to discriminate motor unit spike trains. The summation of motor unit spike trains detected for each muscle was bandpass filtered between 3 to 10 Hz to isolate the tremor related components of the neural drive to muscles. The estimated tremorogenic neural drive was used as input to a PLL that tracked the phase differences between the two muscle groups. The online estimated phase difference was compared with the phase calculated offline using a Hilbert Transform as a ground truth. The results showed a rate of agreement of 0.88 ± 0.22 between offline and online EMG decomposition. The PLL tracked the phase difference of tremor signals in real-time with an average correlation of 0.86 ± 0.16 with the ground truth (average error of 6.40° ± 3.49°). Finally, the online decomposition and phase estimation components were integrated with an electrical stimulator and applied in closed-loop on one patient, to representatively demonstrate the working principle of the full tremor suppression system. The results of this study support the feasibility of real-time estimation of the phase of tremorogenic neural drive to muscles, providing a methodology for future tremor-suppression neuroprostheses.

Distribution of tremorogenic activity among the major superficial muscles of the upper limb in persons with Essential tremor.

OBJECTIVE: Peripheral tremor suppression has the potential to reduce tremor, but we do not currently know where best to intervene. The purpose of this study was to characterize the distribution of tremorogenic activity among upper-limb muscles. METHODS: Surface electromyography was recorded from the 15 major superficial muscles of the upper limb while 25 patients with Essential Tremor performed postural and kinetic tasks. We defined tremorogenic activity as power in the tremor band (4-8 Hz) and determined the distribution of this power among muscles. RESULTS: The distribution varied considerably between patients (mean r = 0.58), but on average, the greatest power was found in the anterior deltoid and extensor carpi ulnaris muscles. Other muscles with high power included the extensor carpi radialis, pectoralis major, lateral deltoid, and brachialis muscles. This distribution was similar (mean r ≥ 0.88) for postural and kinetic tremor, various limb configurations, repetitions, and patient characteristics (sex, tremor severity, age of onset, and duration). CONCLUSIONS: We identified a rough pattern in which muscles opposing gravity appeared to have the highest tremor-band power; we hypothesize that the distribution of tremorogenic muscle activity depends in part on the distribution of voluntary activity required by the task. SIGNIFICANCE: Understanding which muscles exhibit the most tremorogenic activity is one of the steps in the pursuit of optimizing peripheral tremor suppression.

The curvature and variability of wrist and arm movements.

The control of wrist rotations is critical for normal upper limb function, yet has received little attention. In this study, we characterized path shape of wrist rotations in order to better understand the biomechanical and neural factors governing their control. Subjects performed step-tracking wrist rotations in eight directions "at a comfortable speed" and "as fast as possible." For comparison, we also analyzed subjects' arm movement paths in a similar task. We found significant differences between wrist and arm movements. Wrist paths were more curved and more variable than arm paths (p < 0.001). The increased curvature and variability can be explained in part by neuromuscular noise (in actuation and sensing) which is known to increase from proximal to distal in the upper limb. The curvature and variability of wrist paths increased with movement speed (p < 0.001), further implicating (signal-dependent) noise. However, noise cannot explain all of our observations. For example, we found that wrist rotations exhibit a systematic pattern: outbound and inbound paths between the same two targets tend to veer to opposite sides of a straight line. We provide evidence indicating that this type of systematic pattern is not likely caused by noise or other neural causes, but may be explained by the unique biomechanics of the wrist.

Distribution of tremor among the major degrees of freedom of the upper limb in subjects with Essential Tremor.

OBJECTIVE: Although Essential Tremor is one of the most common movement disorders, we do not currently know which muscles are most responsible for tremor. Determining this requires multiple steps, one of which is characterizing the distribution of tremor among the degrees of freedom (DOF) of the upper limb. METHODS: Upper-limb motion was recorded while 22 subjects with ET performed postural and kinetic tasks involving a variety of limb configurations. We calculated the mean distribution of tremor among the seven DOF from the shoulder to the wrist, as well as the effect of limb configuration, repetition, and subject characteristics (sex, tremor onset, duration, and severity) on the distribution. RESULTS: On average, kinetic tremor was greatest in forearm pronation-supination and wrist flexion-extension, intermediate in shoulder internal-external rotation and wrist radial-ulnar deviation and then shoulder flexion-extension and elbow flexion-extension, and least in shoulder abduction-adduction. The average distribution of postural tremor was similar except for forearm pronation-supination, which played a smaller role than in kinetic tremor. Limb configuration and subject characteristics did significantly affect tremor, but practically only in forearm pronation-supination and wrist flexion-extension. There were no significant differences between repetitions, indicating that the distribution was consistent over the duration of the experiment. CONCLUSIONS: This paper presents a thorough characterization of tremor distribution from the shoulder to the wrist. SIGNIFICANCE: Understanding which DOF exhibit the most tremor may lead to more targeted peripheral tremor suppression.